Alex J. Gutman - Becoming a Data Head

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"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful." 
Competing on Analytics
Big Data @ Work
The AI Advantage
You’ve heard the hype around data—now get the facts.  In
, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. 
You’ll learn how to: 
Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what’s really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data
is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you’re a business professional, engineer, executive, or aspiring data scientist, this book is for you.

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ISBN: 978-1-119-74174-9

ISBN: 978-1-119-74176-3 (ebk)

ISBN: 978-1-119-74171-8 (ebk)

For my children Allie, William, and Ellen .

Allie was three when she discovered dad was a “doctor.” Puzzled, she looked at me and said, “But, you don't help people… .” In that spirit, I also dedicate this book to you, the reader .

I hope this helps you . —Alex

For Stephen and Melissa —Jordan

About the Authors

Alex J. Gutmanis a data scientist, corporate trainer, Fulbright Specialist grant recipient, and Accredited Professional Statistician® who enjoys teaching a wide variety of data science topics to technical and non-technical audiences. He earned his Ph.D. in applied math from the Air Force Institute of Technology where he currently serves as an adjunct professor.

Jordan Goldmeieris an internationally recognized analytics professional and data visualization expert, author, and speaker. A former chief operations officer at Excel.TV, he has spent years in the data training trenches. He is the author of Advanced Excel Essentials and Dashboards for Excel . His work has been cited by and quoted in the Associated Press, Bloomberg BusinessWeek, and American Express OPEN Forum. He is currently an Excel MVP Award holder, an achievement he's held for six years, allowing him to provide feedback and direction to Microsoft product teams. He once used Excel to save the Air Force $60 million. He is also a volunteer Emergency Medical Technician.

About the Technical Editors

William A. Brennemanis a Research Fellow and the Global Statistics Discipline Leader at Procter & Gamble in the Data and Modeling Sciences Department and an Adjunct Professor of Practice at Georgia Tech in the Stewart School of Industrial and Systems Engineering. Since joining P&G, he has worked on a wide range of projects that deal with statistics applications in his areas of expertise: design and analysis of experiments, robust parameter design, reliability engineering, statistical process control, computer experiments, machine learning, and statistical thinking. He was also instrumental in the development of an in-house statistics curriculum. He received a Ph.D. in Statistics from the University of Michigan, an MS in Mathematics from the University of Iowa, and a BA in Mathematics and Secondary Education from Tabor College. William is a Fellow in both the American Statistical Association (ASA) and the American Society for Quality (ASQ). He has served as ASQ Statistics Division Chair, ASA Quality and Productivity Section Chair, and as Associate Editor for Technometrics . William also has seven years of experience as an educator at the high school and college level.

Jennifer Stirrupis the Founder and CEO of Data Relish, a UK-based AI and Business Intelligence leadership boutique consultancy delivering data strategy and business-focused solutions. Jen is a recognized leading authority in AI and Business Intelligence Leadership, a Fortune 100 global speaker, and has been named as one of the Top 50 Global Data Visionaries, one of the Top Data Scientists to follow on Twitter, and one of the most influential Top 50 Women in Technology worldwide.

Jen has clients in 24 countries on 5 continents, and she holds postgraduate degrees in AI and Cognitive Science. Jen has authored books on data and artificial intelligence and has been featured on CBS Interactive and the BBC as well as other well-known podcasts, such as Digital Disrupted, Run As Radio, and her own Make Your Data Work webinar series.

Jen has also given keynotes for colleges and universities, as well as donated her expertise to charities and non-profits as a Non-Executive Director. All of Jen's keynotes are based on her 20+ years of global experience, dedication, and hard work.

Acknowledgments

I've noticed a trend in acknowledgment sections—the author's spouse is often mentioned at the end. I suppose it's a saving-the-best-for-last gesture, but I promised my wife if I ever wrote a book, I'd mention her first to make it perfectly clear whose contributions mattered most to me. So, to my wife Erin, thank you for your love, encouragement, and smile. As I write this, you are taking our three young children on a bike ride, giving me time to write one final page. (I assure all readers this act is a representative sample of our lives this past year.)

I'd also like to thank my parents, Ed and Nancy, for being the best cheerleaders in whatever I do and for showing me what being a good parent looks like, and to my siblings Ryan, Ross, and Erin for their support.

This book is the culmination of many discussions with friends and colleagues, ranging from whether I should attempt to write a book about data literacy to potential topics that should appear in it. Thank you especially to Altynbek Ismailov, Andy Neumeier, Bradley Boehmke, Brandon Greenwell, Brent Russell, Cade Saie, Caleb Goodreau, Carl Parson, Daniel Uppenkamp, Douglas Clarke, Greg Anderson, Jason Freels, Joel Chaney, Joseph Keller, Justin Maurer, Nathan Swigart, Phil Hartke, Samuel Reed, Shawn Schneider, Stephen Ferro, and Zachary Allen.

I'm also indebted to the hundreds of engineers, business professionals, and data scientists I've interacted with, personally or online, who've taught me how to be a better data scientist and communicator. And to my “students” (colleagues) who have given candid feedback about the courses I've taught, I heard you and I thank you.

I'm fortunate to have many academic and professional mentors who've given me numerous opportunities to find my voice and confidence as a statistician, data scientist, and trainer. Thank you to Jeffery Weir, John Tudorovic, K. T. Arasu, Raymond Hill, Rob Baker, Scott Crawford, Stephen Chambal, Tony White, and William Brenneman (who kindly served as a technical editor on this book). It's impossible not to become wiser hanging around a group like that.

Thanks to the team at Wiley: Jim Minatel for believing in the project and giving us a chance, Pete Gaughan and John Sleeva for guiding us through the process, and the production staff at Wiley for meticulously combing through our chapters. And to our technical editors, William Brenneman and Jen Stirrup, we appreciate your suggestions and expertise. The book is better because of you.

Special thanks to my coauthor Jordan Goldmeier, for one obvious reason (the book in your hands) and one not so obvious. Early in my career, I complained to Jordan that people didn't share my interest in statistics and statistical thinking. He said if I'm bothered by it, then it's my obligation to change it. I've been working to fulfill that obligation ever since.

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